Description Usage Arguments Value See Also Examples
View source: R/fitDistributionsToCIs.R
Finds the best-fit gamma distribution for a given confidence interval; returns the corresponding density, distribution, quantile and sampling functions.
1 | getGammaFromCI(qLow, qUpp, alpha = 0.05, initPars = c(1, 1), maxiter = 1000)
|
qLow |
The observed lower quantile. |
qUpp |
The observed upper quantile. |
alpha |
The confidence level; i.e. the desired coverage is 1-alpha. Defaults to 0.05. |
initPars |
A vector of length 2 giving the initial parameter values (shape & rate) to start the optimisation; defaults to c(1,1). |
maxiter |
Maximum number of iterations for |
A list with 5 elements:
r |
The sampling function. |
d |
The density function. |
p |
The distribution function. |
q |
The quantile function. |
pars |
A vector of length 2 giving the shape and rate for the best-fit gamma distribution ( |
identifyGammaPars
, optim
, dgamma
1 2 3 4 5 6 7 8 9 | n<-getGammaFromCI(qLow=0.82,qUpp=5.14)
print(n$pars) # the fitted parameter values (shape & rate)
n$r(10) # 10 random values from the fitted gamma distribution
n$d(6) # the probability density at x=6 for the gamma distribution
n$p(2) # the cumulative density at x=2 for the fitted gamma distribution
n$q(c(0.25,0.5,0.75)) # the 25th, 50th (median) and 75th percentiles of the fitted distribution
x<-seq(0,8,length=1e3)
y<-n$d(x)
plot(x,y,type="l",xlab="",ylab="density") # density plot for the fitted gamma distribution
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